Model ranking

Which AI model handles Javanese best?

This measures one thing only: how well a model answers in the Javanese category, judged by readers. A model near the bottom here may well be the stronger one for anything else. Every number comes from the arena itself, not from a separate test.

Speaker acceptance

Live standings· not the final ranking

7%
10/150 matches
#ModelPlayedW / L / TPts
1Gemini 3.5 Flash LiteGoogle5of 508 pairs5 / 0 / 015
2GPT-5.6 LunaOpenAI8of 508 pairs5 / 3 / 015
3Claude 4.5 SonnetAnthropic5of 508 pairs3 / 1 / 110
4Gemma 3 12BGoogle6of 508 pairs3 / 3 / 09
5Llama 3.3 70BMeta10of 508 pairs3 / 7 / 09
6GPT OSS 120BOpenAI2of 285 pairs2 / 0 / 06
7Gemma 4 31BGoogle4of 508 pairs2 / 2 / 06
8DeepSeek V4 ProDeepSeek1of 104 pairs1 / 0 / 03
9Claude 4.5 HaikuAnthropic4of 508 pairs0 / 3 / 11
10Nemotron 3 UltraLainnya1of 44 pairs0 / 1 / 00
11Mistral Small 3.2 24BMistral4of 508 pairs0 / 4 / 00
·MiMo-V2.5Lainnya0of 12 pairs0 / 0 / 00
·Mistral Small 3Mistral0of 501 pairs0 / 0 / 00
Standing
: Position by points, exactly as in a league table. It moves with every vote. A dot instead of a number means the model is in the arena but has never been judged, so it has no standing yet.
Played
: How many times this model has actually been judged, out of the pairs it appears in. Read the points next to it together with this: three points from one match says far less than three points from thirty.
Wins, losses, ties
: Raw counted votes. Calibration pairs, whose answer we already know, are excluded because their votes never feed the ranking.
Points
: Three for a win, one for a draw, as in a league table. Equal points are broken by wins minus losses, then by matches played; both are already visible in the W / L / T column. Points do not account for how strong the opponent was: the final rating does, and it replaces this column once enough matches have been played.
Which side an answer appears on is decided by the server and randomised, so a habit of picking one side never becomes a result.

What this does not say

A position here is not a verdict on a model. It is one narrow measurement: how well it answers in the Javanese category, judged by people reading two unlabelled answers.

Models are built for different things, and are trained on very different amounts of Indonesian. One that sits low here may be the far stronger choice for English, for code, for reasoning, or for longer work, none of which this arena touches. A low position means it was less convincing on these questions, in this variety, to the people who voted. Nothing beyond that.

Where these numbers come from

Every row above was produced by people reading two unlabelled answers and picking one. There is no other source.

counted votes
25
people
3
models in the arena
13
Add your vote